Fault diagnosis method based on rough set and least squares support vector machine and its application
Shaohua Jiang · Journal of Central South University(Science and Technology) · 2009
Aiming at the complex and variable reaction of Pb-Zn smelting in imperial smelting furnace(ISF), a novel method for the furnace fault diagnosis based on rough set(RS) and least squares support vector machine(LS-SVM) was put forward.According to the method, the original fault examples were reduced by using the rough set theory to get a simple rule collection as eigenvectors, and then these eigenvectors were input into multiple fault classifiers of LS-SVM to identify faults.The experimental results show that the method has better classification performance and its classification precision reaches more than 90%.